基于互联网搜索数据研究全球高致病性禽流感病毒H5N1的暴发监测

发布时间：2019-05-11 14:02

【摘要】：目的分析互联网搜索数据与高致病性禽流感病毒H5N1的关系,探讨利用网络搜索工具对其监测和预警的可能性。方法基于联合国粮食及农业组织(Food and Agriculture Organization of the United Nations,FAO)和世界动物卫生组织(World Organization for Animal Health,OIE)收集整合了2004-2009年全球高致病性禽流感病毒H5N1在家禽中的暴发数据,从Google Trends获取同时期的相关关键词数据。在对二者的数据进行描述分析与对比的基础上,计算Spearman等级相关系数评价其相关程度,并通过平移技术以相关系数为指标分析互联网数据预测H5N1暴发的时间提前期。结果以2004-2009年为整体,互联网数据与H5N1的相关性并不高(r=0.276,t=3.57,P0.001),但年度数据则均表现出了较强的相关性,2004-2009年相关性系数分别为r2004=0.718(t=3.64,P0.001),r2005=0.576(t=3.58,P0.001),r2006=0.760(t=3.62,P0.001),r2007=0.474(t=3.45,P0.001),r2008=0.750(t=3.47,P0.001),r2009=-0.442(t=3.32,P=0.001)。且在各个年份中,将OIE/FAO流感监测数据提前1~4周后出现与Google Trends监测数据的相关系数最大值,可认为Google Trends数据可提前1~4周预测H5N1暴发的趋势。结论利用互联网搜索数据预测高致病性禽流感病毒H5N1的暴发可作为传统方法的补充手段,但由于搜索技术等的限制该方法仍需进行进一步的改进以提高准确性,其思路可推广至其他传染性疾病暴发的监测与预警。
[Abstract]:Objective to analyze the relationship between Internet search data and highly pathogenic avian influenza virus (H5N1), and to explore the possibility of monitoring and early warning by Internet search tools. Methods based on the Food and Agriculture Organization of the United Nations (Food and Agriculture Organization of the United Nations,FAO) and the World Organization for Animal Health (World Organization for Animal Health,OIE), the outbreak data of the global highly pathogenic avian influenza virus H5N1 in poultry from 2004 to 2009 were collected and integrated. The relevant keyword data of the same period were obtained from Google Trends. On the basis of describing, analyzing and comparing the data of the two, the correlation degree of Spearman grade correlation coefficient is calculated, and the time lead time of H5N1 outbreak predicted by Internet data is analyzed by translation technique with correlation coefficient as index. Results in 2004-2009 as a whole, the correlation between Internet data and H5N1 was not high (r = 0.276, t = 3.57, P 0.001), but the annual data showed a strong correlation, and the correlation coefficients for 2004-2009 were r 20040.718 (t = 3.64, P < 0.001), and the correlation coefficients of the data from 2004 to 2009 were not significant (r = 0.276, t = 3.57, P < 0.001). P 0.001), r 2005 / 0.576 (t = 3.58, P 0.001), r 2006 / 0.760 (t = 3.62, P 0.001), r 2007 / 0.474 (t = 3.45, P 0.001), r 2008 / 0.750 (t = 3.47, P 0.001), r 2009 / 0.442 (t = 3.32, P < 0.001). In each year, the maximum correlation coefficient between OIE/FAO influenza surveillance data and Google Trends surveillance data appeared 1 脳 4 weeks ahead of schedule, and it can be considered that Google Trends data can predict the trend of H5N1 outbreak one or four weeks ahead of schedule. Conclusion using Internet search data to predict the outbreak of highly pathogenic avian influenza virus H5N1 can be used as a supplement to the traditional method, but due to the limitation of search technology, this method still needs to be further improved to improve the accuracy. The idea can be extended to the monitoring and early warning of other infectious disease outbreaks.
【作者单位】：复旦大学公共卫生学院流行病学教研室教育部公共卫生安全重点实验室;
【基金】：国家自然科学基金(81102167) 上海市新优青计划(XYQ2013071) 复旦大学自主科研项目(20520133105) 全国优秀博士学位论文作者专项资金(201186)
【分类号】：R511.7

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